Choosing Your AI Copilot: Maximizing Developer Productivity

Abstract

The AI coding agent landscape evolves weekly. This talk compares today’s frontrunners, shows where each shines, and shares prompts, policies, and “rules templates” that turn code suggestions into production-quality output. Equip your team to select, tune, and measure the AI copilots that truly elevate velocity and code quality.

Main Takeaways

  1. Understand the strengths and weaknesses of today’s top AI coding agents
  2. Learn the best strategies and tricks for consistently producing high-quality outputs.

Interview:

What is the focus of your work these days?

Staying on top of the latest AI tool releases and getting hands-on with them to cut through the noise and figure out what’s actually useful. I then turn those insights into content and lectures to help others learn and apply the tools effectively.

What is the motivation behind your talk?

It can be overwhelming to navigate the fast-moving world of AI tools. I often see developers either waste time due to a lack of awareness of existing tools or miss out on their full potential. This talk is meant to simplify the landscape, share practical techniques, and help maximize the value gained from AI copilots.

Who is the target audience for this session?

Software Engineers, Product Managers, AI enthusiasts, and technical leaders looking to maximize engineering productivity with GenAI.


Speaker

Sepehr Khosravi

Machine Learning Platform Engineer @Coinbase, Instructor @UC Berkeley - 1st Vibe Coding Course

Sepehr Khosravi is a software engineer at Coinbase working on machine learning infrastructure, and an instructor at UC Berkeley where he teaches courses on generative AI and rapid product development. He's also the founder of AI Scouts, a free program teaching students how to build AI-powered apps from scratch.

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